Documentation updated

This commit is contained in:
fjosw 2022-02-09 11:39:14 +00:00
parent 877396080d
commit cd25125f2c
3 changed files with 98 additions and 98 deletions

View file

@ -53,6 +53,9 @@
<li>
<a class="function" href="#load_object">load_object</a>
</li>
<li>
<a class="function" href="#pseudo_Obs">pseudo_Obs</a>
</li>
<li>
<a class="function" href="#gen_correlated_data">gen_correlated_data</a>
</li>
@ -112,6 +115,38 @@
<span class="k">return</span> <span class="n">pickle</span><span class="o">.</span><span class="n">load</span><span class="p">(</span><span class="n">file</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">pseudo_Obs</span><span class="p">(</span><span class="n">value</span><span class="p">,</span> <span class="n">dvalue</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">samples</span><span class="o">=</span><span class="mi">1000</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Generate an Obs object with given value, dvalue and name for test purposes</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> value : float</span>
<span class="sd"> central value of the Obs to be generated.</span>
<span class="sd"> dvalue : float</span>
<span class="sd"> error of the Obs to be generated.</span>
<span class="sd"> name : str</span>
<span class="sd"> name of the ensemble for which the Obs is to be generated.</span>
<span class="sd"> samples: int</span>
<span class="sd"> number of samples for the Obs (default 1000).</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">if</span> <span class="n">dvalue</span> <span class="o">&lt;=</span> <span class="mf">0.0</span><span class="p">:</span>
<span class="k">return</span> <span class="n">Obs</span><span class="p">([</span><span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">(</span><span class="n">samples</span><span class="p">)</span> <span class="o">+</span> <span class="n">value</span><span class="p">],</span> <span class="p">[</span><span class="n">name</span><span class="p">])</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">for</span> <span class="n">_</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">100</span><span class="p">):</span>
<span class="n">deltas</span> <span class="o">=</span> <span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">normal</span><span class="p">(</span><span class="mf">0.0</span><span class="p">,</span> <span class="n">dvalue</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">samples</span><span class="p">),</span> <span class="n">samples</span><span class="p">)]</span>
<span class="n">deltas</span> <span class="o">-=</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">deltas</span><span class="p">)</span>
<span class="n">deltas</span> <span class="o">*=</span> <span class="n">dvalue</span> <span class="o">/</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">((</span><span class="n">np</span><span class="o">.</span><span class="n">var</span><span class="p">(</span><span class="n">deltas</span><span class="p">)</span> <span class="o">/</span> <span class="n">samples</span><span class="p">))</span> <span class="o">/</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">1</span> <span class="o">+</span> <span class="mi">3</span> <span class="o">/</span> <span class="n">samples</span><span class="p">)</span>
<span class="n">deltas</span> <span class="o">+=</span> <span class="n">value</span>
<span class="n">res</span> <span class="o">=</span> <span class="n">Obs</span><span class="p">(</span><span class="n">deltas</span><span class="p">,</span> <span class="p">[</span><span class="n">name</span><span class="p">])</span>
<span class="n">res</span><span class="o">.</span><span class="n">gamma_method</span><span class="p">(</span><span class="n">S</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">tau_exp</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
<span class="k">if</span> <span class="nb">abs</span><span class="p">(</span><span class="n">res</span><span class="o">.</span><span class="n">dvalue</span> <span class="o">-</span> <span class="n">dvalue</span><span class="p">)</span> <span class="o">&lt;</span> <span class="mf">1e-10</span> <span class="o">*</span> <span class="n">dvalue</span><span class="p">:</span>
<span class="k">break</span>
<span class="n">res</span><span class="o">.</span><span class="n">_value</span> <span class="o">=</span> <span class="nb">float</span><span class="p">(</span><span class="n">value</span><span class="p">)</span>
<span class="k">return</span> <span class="n">res</span>
<span class="k">def</span> <span class="nf">gen_correlated_data</span><span class="p">(</span><span class="n">means</span><span class="p">,</span> <span class="n">cov</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">tau</span><span class="o">=</span><span class="mf">0.5</span><span class="p">,</span> <span class="n">samples</span><span class="o">=</span><span class="mi">1000</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot; Generate observables with given covariance and autocorrelation times.</span>
@ -251,6 +286,68 @@ path to the file</li>
</div>
</section>
<section id="pseudo_Obs">
<div class="attr function"><a class="headerlink" href="#pseudo_Obs">#&nbsp;&nbsp</a>
<span class="def">def</span>
<span class="name">pseudo_Obs</span><span class="signature">(value, dvalue, name, samples=1000)</span>:
</div>
<details>
<summary>View Source</summary>
<div class="codehilite"><pre><span></span><span class="k">def</span> <span class="nf">pseudo_Obs</span><span class="p">(</span><span class="n">value</span><span class="p">,</span> <span class="n">dvalue</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">samples</span><span class="o">=</span><span class="mi">1000</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Generate an Obs object with given value, dvalue and name for test purposes</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> value : float</span>
<span class="sd"> central value of the Obs to be generated.</span>
<span class="sd"> dvalue : float</span>
<span class="sd"> error of the Obs to be generated.</span>
<span class="sd"> name : str</span>
<span class="sd"> name of the ensemble for which the Obs is to be generated.</span>
<span class="sd"> samples: int</span>
<span class="sd"> number of samples for the Obs (default 1000).</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">if</span> <span class="n">dvalue</span> <span class="o">&lt;=</span> <span class="mf">0.0</span><span class="p">:</span>
<span class="k">return</span> <span class="n">Obs</span><span class="p">([</span><span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">(</span><span class="n">samples</span><span class="p">)</span> <span class="o">+</span> <span class="n">value</span><span class="p">],</span> <span class="p">[</span><span class="n">name</span><span class="p">])</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">for</span> <span class="n">_</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">100</span><span class="p">):</span>
<span class="n">deltas</span> <span class="o">=</span> <span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">normal</span><span class="p">(</span><span class="mf">0.0</span><span class="p">,</span> <span class="n">dvalue</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">samples</span><span class="p">),</span> <span class="n">samples</span><span class="p">)]</span>
<span class="n">deltas</span> <span class="o">-=</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">deltas</span><span class="p">)</span>
<span class="n">deltas</span> <span class="o">*=</span> <span class="n">dvalue</span> <span class="o">/</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">((</span><span class="n">np</span><span class="o">.</span><span class="n">var</span><span class="p">(</span><span class="n">deltas</span><span class="p">)</span> <span class="o">/</span> <span class="n">samples</span><span class="p">))</span> <span class="o">/</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">1</span> <span class="o">+</span> <span class="mi">3</span> <span class="o">/</span> <span class="n">samples</span><span class="p">)</span>
<span class="n">deltas</span> <span class="o">+=</span> <span class="n">value</span>
<span class="n">res</span> <span class="o">=</span> <span class="n">Obs</span><span class="p">(</span><span class="n">deltas</span><span class="p">,</span> <span class="p">[</span><span class="n">name</span><span class="p">])</span>
<span class="n">res</span><span class="o">.</span><span class="n">gamma_method</span><span class="p">(</span><span class="n">S</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">tau_exp</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
<span class="k">if</span> <span class="nb">abs</span><span class="p">(</span><span class="n">res</span><span class="o">.</span><span class="n">dvalue</span> <span class="o">-</span> <span class="n">dvalue</span><span class="p">)</span> <span class="o">&lt;</span> <span class="mf">1e-10</span> <span class="o">*</span> <span class="n">dvalue</span><span class="p">:</span>
<span class="k">break</span>
<span class="n">res</span><span class="o">.</span><span class="n">_value</span> <span class="o">=</span> <span class="nb">float</span><span class="p">(</span><span class="n">value</span><span class="p">)</span>
<span class="k">return</span> <span class="n">res</span>
</pre></div>
</details>
<div class="docstring"><p>Generate an Obs object with given value, dvalue and name for test purposes</p>
<h6 id="parameters">Parameters</h6>
<ul>
<li><strong>value</strong> (float):
central value of the Obs to be generated.</li>
<li><strong>dvalue</strong> (float):
error of the Obs to be generated.</li>
<li><strong>name</strong> (str):
name of the ensemble for which the Obs is to be generated.</li>
<li><strong>samples</strong> (int):
number of samples for the Obs (default 1000).</li>
</ul>
</div>
</section>
<section id="gen_correlated_data">
<div class="attr function"><a class="headerlink" href="#gen_correlated_data">#&nbsp;&nbsp</a>

View file

@ -281,9 +281,6 @@
<li>
<a class="function" href="#covariance">covariance</a>
</li>
<li>
<a class="function" href="#pseudo_Obs">pseudo_Obs</a>
</li>
<li>
<a class="function" href="#import_jackknife">import_jackknife</a>
</li>
@ -1775,38 +1772,6 @@
<span class="k">return</span> <span class="n">dvalue</span>
<span class="k">def</span> <span class="nf">pseudo_Obs</span><span class="p">(</span><span class="n">value</span><span class="p">,</span> <span class="n">dvalue</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">samples</span><span class="o">=</span><span class="mi">1000</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Generate an Obs object with given value, dvalue and name for test purposes</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> value : float</span>
<span class="sd"> central value of the Obs to be generated.</span>
<span class="sd"> dvalue : float</span>
<span class="sd"> error of the Obs to be generated.</span>
<span class="sd"> name : str</span>
<span class="sd"> name of the ensemble for which the Obs is to be generated.</span>
<span class="sd"> samples: int</span>
<span class="sd"> number of samples for the Obs (default 1000).</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">if</span> <span class="n">dvalue</span> <span class="o">&lt;=</span> <span class="mf">0.0</span><span class="p">:</span>
<span class="k">return</span> <span class="n">Obs</span><span class="p">([</span><span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">(</span><span class="n">samples</span><span class="p">)</span> <span class="o">+</span> <span class="n">value</span><span class="p">],</span> <span class="p">[</span><span class="n">name</span><span class="p">])</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">for</span> <span class="n">_</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">100</span><span class="p">):</span>
<span class="n">deltas</span> <span class="o">=</span> <span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">normal</span><span class="p">(</span><span class="mf">0.0</span><span class="p">,</span> <span class="n">dvalue</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">samples</span><span class="p">),</span> <span class="n">samples</span><span class="p">)]</span>
<span class="n">deltas</span> <span class="o">-=</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">deltas</span><span class="p">)</span>
<span class="n">deltas</span> <span class="o">*=</span> <span class="n">dvalue</span> <span class="o">/</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">((</span><span class="n">np</span><span class="o">.</span><span class="n">var</span><span class="p">(</span><span class="n">deltas</span><span class="p">)</span> <span class="o">/</span> <span class="n">samples</span><span class="p">))</span> <span class="o">/</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">1</span> <span class="o">+</span> <span class="mi">3</span> <span class="o">/</span> <span class="n">samples</span><span class="p">)</span>
<span class="n">deltas</span> <span class="o">+=</span> <span class="n">value</span>
<span class="n">res</span> <span class="o">=</span> <span class="n">Obs</span><span class="p">(</span><span class="n">deltas</span><span class="p">,</span> <span class="p">[</span><span class="n">name</span><span class="p">])</span>
<span class="n">res</span><span class="o">.</span><span class="n">gamma_method</span><span class="p">(</span><span class="n">S</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">tau_exp</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
<span class="k">if</span> <span class="nb">abs</span><span class="p">(</span><span class="n">res</span><span class="o">.</span><span class="n">dvalue</span> <span class="o">-</span> <span class="n">dvalue</span><span class="p">)</span> <span class="o">&lt;</span> <span class="mf">1e-10</span> <span class="o">*</span> <span class="n">dvalue</span><span class="p">:</span>
<span class="k">break</span>
<span class="n">res</span><span class="o">.</span><span class="n">_value</span> <span class="o">=</span> <span class="nb">float</span><span class="p">(</span><span class="n">value</span><span class="p">)</span>
<span class="k">return</span> <span class="n">res</span>
<span class="k">def</span> <span class="nf">import_jackknife</span><span class="p">(</span><span class="n">jacks</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">idl</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Imports jackknife samples and returns an Obs</span>
@ -4977,68 +4942,6 @@ is constrained to the maximum value.</p>
</div>
</section>
<section id="pseudo_Obs">
<div class="attr function"><a class="headerlink" href="#pseudo_Obs">#&nbsp;&nbsp</a>
<span class="def">def</span>
<span class="name">pseudo_Obs</span><span class="signature">(value, dvalue, name, samples=1000)</span>:
</div>
<details>
<summary>View Source</summary>
<div class="codehilite"><pre><span></span><span class="k">def</span> <span class="nf">pseudo_Obs</span><span class="p">(</span><span class="n">value</span><span class="p">,</span> <span class="n">dvalue</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">samples</span><span class="o">=</span><span class="mi">1000</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Generate an Obs object with given value, dvalue and name for test purposes</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> value : float</span>
<span class="sd"> central value of the Obs to be generated.</span>
<span class="sd"> dvalue : float</span>
<span class="sd"> error of the Obs to be generated.</span>
<span class="sd"> name : str</span>
<span class="sd"> name of the ensemble for which the Obs is to be generated.</span>
<span class="sd"> samples: int</span>
<span class="sd"> number of samples for the Obs (default 1000).</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">if</span> <span class="n">dvalue</span> <span class="o">&lt;=</span> <span class="mf">0.0</span><span class="p">:</span>
<span class="k">return</span> <span class="n">Obs</span><span class="p">([</span><span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">(</span><span class="n">samples</span><span class="p">)</span> <span class="o">+</span> <span class="n">value</span><span class="p">],</span> <span class="p">[</span><span class="n">name</span><span class="p">])</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">for</span> <span class="n">_</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">100</span><span class="p">):</span>
<span class="n">deltas</span> <span class="o">=</span> <span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">normal</span><span class="p">(</span><span class="mf">0.0</span><span class="p">,</span> <span class="n">dvalue</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">samples</span><span class="p">),</span> <span class="n">samples</span><span class="p">)]</span>
<span class="n">deltas</span> <span class="o">-=</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">deltas</span><span class="p">)</span>
<span class="n">deltas</span> <span class="o">*=</span> <span class="n">dvalue</span> <span class="o">/</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">((</span><span class="n">np</span><span class="o">.</span><span class="n">var</span><span class="p">(</span><span class="n">deltas</span><span class="p">)</span> <span class="o">/</span> <span class="n">samples</span><span class="p">))</span> <span class="o">/</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">1</span> <span class="o">+</span> <span class="mi">3</span> <span class="o">/</span> <span class="n">samples</span><span class="p">)</span>
<span class="n">deltas</span> <span class="o">+=</span> <span class="n">value</span>
<span class="n">res</span> <span class="o">=</span> <span class="n">Obs</span><span class="p">(</span><span class="n">deltas</span><span class="p">,</span> <span class="p">[</span><span class="n">name</span><span class="p">])</span>
<span class="n">res</span><span class="o">.</span><span class="n">gamma_method</span><span class="p">(</span><span class="n">S</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">tau_exp</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
<span class="k">if</span> <span class="nb">abs</span><span class="p">(</span><span class="n">res</span><span class="o">.</span><span class="n">dvalue</span> <span class="o">-</span> <span class="n">dvalue</span><span class="p">)</span> <span class="o">&lt;</span> <span class="mf">1e-10</span> <span class="o">*</span> <span class="n">dvalue</span><span class="p">:</span>
<span class="k">break</span>
<span class="n">res</span><span class="o">.</span><span class="n">_value</span> <span class="o">=</span> <span class="nb">float</span><span class="p">(</span><span class="n">value</span><span class="p">)</span>
<span class="k">return</span> <span class="n">res</span>
</pre></div>
</details>
<div class="docstring"><p>Generate an Obs object with given value, dvalue and name for test purposes</p>
<h6 id="parameters">Parameters</h6>
<ul>
<li><strong>value</strong> (float):
central value of the Obs to be generated.</li>
<li><strong>dvalue</strong> (float):
error of the Obs to be generated.</li>
<li><strong>name</strong> (str):
name of the ensemble for which the Obs is to be generated.</li>
<li><strong>samples</strong> (int):
number of samples for the Obs (default 1000).</li>
</ul>
</div>
</section>
<section id="import_jackknife">
<div class="attr function"><a class="headerlink" href="#import_jackknife">#&nbsp;&nbsp</a>

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